1. Linear regression (20 #) Simple linear regression is a useful approach for predicting a response on the basis of a single predictor variable and takes the formy = , + B,x + 5 . Suppose a data set containing 3 observations {(x,,v.): (1, 5), (0, 3), (-1, -2); and the least squares coefficient estimates are 2 for Bo and 3 for , on the basis of the data set. Please calculate the R" statistic based on the estimates and analyze how much proportion of variability in response y can be explained using x? Note that Ri -ISS-RSS where the total swan of squares TSS- > (y, - y) , the sum of squared TSS residuals RSS=)() - v.)' and n is the number of the observations (in this case / 3). 1/1 A W EN